class_docstr: Abstract Layer for tensorflow_text tokenizers.
  
  Input shape:
    N-D (2D as default) tensor with shape: `(batch_size, input_length)`.
  
  Output shape:
    (N+1)-D (3D as default) tensor with shape:
      `(batch_size, input_length, token_dim)`.
code: def get_config(self):
      config = {
          "pad_value": self._pad_value,
          "squeeze_token_dim": self._squeeze_token_dim,
      }
      base_config = super(TokenizerBase, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
imports: import os
  import tensorflow
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.ops.ragged import ragged_conversion_ops
  from tensorflow_text.python.ops import unicode_script_tokenizer
  from tensorflow_text.python.ops import whitespace_tokenizer
  from tensorflow_text.python.ops import wordpiece_tokenizer
label_desc: Use image node_id 7 for calling the TokenizerBase obj's underlying member method code with example usage: obj.get_config() and returns: dict